HIV-1 reverse transcriptase is an multifunctional enzyme which is involved in the catalytic transformation of single-stranded viral RNA into double-stranded DNA to be then integrated into the host cell DNA. Several drugs, such as AZT and DDI, have been used to inhibit this enzyme; however, due to their side effects such as toxicity and the rapid emergence of resistant strains, new chemotherapeutic agents need to be developed. Due to the successful nature of computer-aided drug design in the identification of potential drug candidates on other enzymatic systems, our group and collaborators have decided to pursue this route to find possible inhibitors for HIV-1 reverse transcriptase. The x-ray structural data of the double-stranded DNA/ HIV-1 RT and the apoprotein have been made available to us through our collaboration with Edward Arnold at Rutgers University. With this 3D structure of HIV-1 RT, Tack Kuntz's group at UCSF have been able to use computational methods to find interesting pockets, including other sites than the active site, for potential drug targets. Due to the mutations which occur, our focus would be on the highly conserved regions of the enzyme. These sites will then be run using the DOCK program developed in the Kuntz's group to find potential targets. Although my primary role is the organic chemist on this project, I need to have access to the graphics system to use the various programs, primarily MIDAS, for viewing the results obtained from the DOCK runs as well as any additional compounds synthesized in the lab. The USCF Computer Graphics Laboratory system provides an indispensable service necessary for this research and assists us in the development of potential leads. Once the initial testing has been completed, the use of the experimental and computational data to modify the best candidates would, therefore, enhance our understanding of the interaction of inhibitors and enzyme and further our investigation into potential chemotherapeutic agents of HIV-1 RT.